0

The Influences of Bettors Personality Traits on Betting Decision-making

Behaviors for Sports Lottery

()

()

630 (structure equation modeling, SEM) (confirmatory factor analysis, CFA)

1

Abstract Based on the speculative essential of sports lottery and the perspective of

behavioral finance, the lottery betting decision could be regarded as a mental decision-making process, and the bettors behaviors were simultaneously influenced by the complex internal and external factors, such as psychological traits and socio-demographics, so that the causes and the criteria of betting decisions would vary. Namely, betting in the bounded rational decision-making processes, the sports lottery bettors might appear various behavioral biases. Whether the betting decision-making process of bettor exhibit herding bias? Or would bettors herding be caused by their own psychological traits or demographics? All of these issues were deserved to be concerned and further investigated. However, in the previous literature, there were still a lot of arguments regarding the bettors decision-making behaviors required to be clarified; the relevant literature associated with multidiscipline applying to elaborate the bettors behaviors of betting sports lottery was rarely proposed. In light of these reasons, this current study attempts to explore the internal and external factors associated with the herding behavior of sports lottery by incorporating the interdisciplinary perspectives including sociology, psychology, rational decision-making behavioral finance and lottery gambling theory. Furthermore, following stratified proportional random sampling and quota sampling methods, the on-site of sports lottery bettors (n=630) at national-wide retail channels responded the questionnaire to conduct a structure equation modeling (SEM) analysis. In the confirmatory factor analysis (CFA), the goodness-of-fit on the measures are revealed. The results elucidated how the bettors psychological traits and socio-demographics impact on their herding behaviors. The study concluded with suggestions to enhance the in-depth comprehension of bettors behaviors that the sports lottery business most concerned.

Key words: sports lottery; personality traits; socio-demographics; bounded

rational; behavioral bias

2

(2009) 2009 6

2012 16 1 6 (2013)

(Graeme, 1995) (Forrest & Simmons, 2003) (20042007) 2009 (rational decision-making process)

201020082009 (2006)

(2006) (speculate) (Matheson, 2001)

3

(gamblers fallacy) (2006Clotfelter & Cook, 1993; Terrell, 1994; Papachristou, 2004; Williams, 2005) Williams Connolly (2006)Pelletier Ladouceur (2007)

(Sevigny & Ladoucer, 2003)

(2011)

(herding)

() (

4

) () ()

(rationality) (bounded rational)

(Shafir & LeBoeuf, 2002)

(Daft, 2003; Osland, Kolb, Rubin, & Turner, 2006; Robbins, 2002) Robbins (2002) 1.2.3.4.5.6. (Hammond, Keeney, & Raiffa, 2002) Mintzberg, RaisinghaniTheoret (1976)

Simon (1956)

5

(Guryan & Kearney, 2008) (efficient market hypothesis,

EMH)

(Fama, 1965) (prospect theory) (behavioral finance)

(Kahneman & Tverskey, 1979)

:

(lottery gambling)

Ariyabuddhiphongs (2011)

(Clotfelter & Cook, 1989) Lam (2007)MiyazakiBrumbaughSprott (1999)

6

(Forrest, Simmons, & Chesters, 2002) (Ariyabuddhiphongs & Chanchalermporn, 2007) (Tversky & Kahneman, 1974, 1981) (Griffiths & Wood, 2001) (Nyman, 2004)

(representativeness heuristic) (label effect)

(anchoring effect) (2008) Rogers (1998)

(unrealistic optimism) (superstitious belief) (illusion of control)

(Trevorrow & Moore, 1998) (Vander Bilt, Dodge, Pandav, Shaffer, & Ganguli, 2004 ) (McNeilly & Burke, 2001) Wickwire, Jr., Whelan, West, Meyer, McCauslandLuellen (2007)

(Bruyneel, Dewitte, Franses, & Dekimpe, 2006)

(Cook, McHenry, & Leigh, 1998) Balabanis (2002)

7

(Welte, Barnes, Wieczorek, Tidwell, & Parker, 2002) (Hing & Breen, 2001; Ariyabuddhiphongs, 2006) KaizelerFaustino (2008) ForrestGuley (2009) (Clotfelter & Cook, 1989, 1990; Jackson, 1994; Kitchen & Powells, 1991) (personality traits)

(Allport, 1937)

(Costa & McCrace, 1992)

(Pervin, 1993) Rotter (1966)

MyersMcCaulley (1985) ////Bailard, BiehlKaiser (1986)

CostaMcCrace (1992) (neuroticism) (extroversion) (openness) (agreeableness) (conscientiousness)

8

(Schreurs, Druart, Proost, & De Witte, 2009)

(Fung & Ng, 2006) Lamb, Chuang, Wessels, BrobergHuang (2002)Rantanen, Metspelto, Feldt, PulkkinenKokko (2007) Allemand, ZimprichHertzog (2007)

Rantanen (2007)

Lochbaum, Rhodes, Stevenson, Surlesd, StevensWang (2010) (herding behavior)

(behavioral bias) Sherif (1966)

(2003)

(2003) (conformity) (Allen, 1965) (informational social influence) (normative social influence) (Bearden, Netemeyer, & Teel, 1989)

9

(Wilkie, 1994 ; Macinnis, 1997) (Park & Lessig, 1977)

(private information) (Banerjee, 1992 ; Bikhchandani, Hirshleifer, & Welch, 1992 )

Sias (2004)1. (reputational herding)

2. (information cascade)

3. (investigative herding)

4. (fads) 5. (characteristics herding)

Adams (2001)

10

(Coups, Haddock, & Webley, 1998) (2008)

(

)

Crutchfield (1955) SnyderIckes (1985)

EaglyCarli (1981)

(Jahoda, 1959) Asch (1951)

LascuZinkhan (1999)

BeardenRose (1990)

Menkhoff, SchmidtBrozynski (2006)

11

(Caplin & Leahy, 2001; Elster, 1998) Nicholson, Soane, Fenton-O'CreevyWillman (2005)

(Schaefer, Williams, Goodie, & Campbell, 2004)

(social embeddedness)

(Aasved, 2003; Browne & Brown, 1994; Gupta & Derevensky, 1997; Herring & Bledsoe, 1994; Lim & Lee, 2009; Moore & Ohtsuka, 1997)

(Baddeley, 2010; DellaVigna, 2009; Sehgal & Tripathi, 2009) Stone, DodrillJohnson (2001)

Nicholson(2005)

(Chantal & Vallerand, 1996; Griffiths et al., 2009; Herring & Bledsoe, 1994; Rogers, 1998; Stinchfield, Cassuto, Winters, & Latimer, 1997)

12

(cross section)

1

1

()

1

1

NEO-FFI

Allport (1937) ; CostaMcCrace (1992)

13

(2008)Bearden, NetemeyerTeel (1989) ; Sherif (1966)

()

CostaMcCrae (1992) (NEO Five-Factor Inventory, NEO-FFI) 4151

BeardenNetemeyerTeel (1989) 5511064

(double translation) 3

()

14

19

1 2 ()

19 1059 ( 56.5%21.2%20.2%2.1%)

()

(structural equation modeling, SEM)

Bagozzi (1980) (2002)

Schumacker Lomax (1996) 200 500

(2002) (2006) 300

630

15

95%[1/] =3.98%

AndersonGerbing (1988)

(two-step structural equation modeling) (confirmatory factor analysis, CFA) ()

SEM (model identification) (principle of parsimony)Bollen (1989) (multiple indicator multiple cause, MIMIC) () (maximum likelihood) (goodness of fit)

(squared multiple correlation, SMC) (composite reliability; CR) (average variance extracted, AVE) Hair, Black, Babin, AndersonTatham (2006) (offending estimates)

(principle of parsimony) SFLSMC

2

16

(standardized factor loading, SFL) .59.87.95 (standardized error variance, SEV) (standard deviation, SD) (0.0200.054)

2 SFL SD t SEV SD t SMC Cronbachs CR AVE

N1 0.78 0.033 20.69* 0.39 0.030 12.26* 0.56

0.80 0.81 0.59 N2 0.87 0.033 25.30* 0.25 0.036 4.23* 0.83 N3 0.64 0.037 17.05* 0.59 0.037 16.49* 0.39

E1 0.64 0.038 11.07* 0.58 0.046 10.49* 0.40

0.80 0.80 0.51 E2 0.62 0.036 10.30* 0.62 0.045 10.81* 0.35 E3 0.77 0.045 13.96* 0.41 0.051 8.19* 0.58 E4 0.80 0.043 15.59* 0.35 0.049 5.96* 0.70

O1 0.62 0.037 10.36* 0.62 0.046 9.83* 0.35

0.76 0.76 0.52 O2 0.73 0.053 5.51* 0.46 0.054 12.89* 0.63 O3 0.81 0.045 6.04* 0.35 0.050 12.63* 0.60

A1 0.62 0.031 11.24* 0.61 0.041 11.14* 0.38

0.85 0.85 0.53 A2 0.85 0.020 17.46* 0.28 0.036 7.12* 0.74 A3 0.80 0.022 16.50* 0.36 0.038 8.25* 0.68 A4 0.75 0.027 13.59* 0.44 0.040 10.34* 0.52 A5 0.61 0.034 10.68* 0.63 0.043 11.28* 0.35

C1 0.63 0.046 11.43* 0.60 0.039 11.44* 0.38

0.90 0.90 0.52

C2 0.71 0.042 13.46* 0.50 0.030 10.99* 0.49 C3 0.71 0.044 13.84* 0.49 0.033 10.88* 0.51 C4 0.64 0.044 11.72* 0.59 0.035 11.38* 0.40 C5 0.66 0.044 12.55* 0.57 0.034 11.21* 0.44 C6 0.77 0.037 15.31* 0.41 0.021 10.36* 0.59 C7 0.80 0.038 16.49* 0.35 0.021 9.89* 0.65 C8 0.73 0.047 14.20* 0.47 0.030 10.77* 0.53 C9 0.72 0.043 14.10* 0.48 0.031 10.80* 0.53

H1 0.80 0.043 8.70* 0.35 0.028 9.81* 0.49

0.80 0.80 0.50 H2 0.73 0.045 12.06* 0.47 0.036 7.57* 0.71 H3 0.67 0.048 11.15* 0.55 0.042 8.86* 0.35 H4 0.62 0.049 10.20* 0.62 0.044 9.71* 0.31

H5 0.67 0.045 12.50* 0.55 0.036 11.01* 0.44

0.86 0.87 0.55

H6 0.79 0.044 15.78* 0.37 0.029 9.64* 0.64 H7 0.79 0.045 15.51* 0.38 0.033 9.27* 0.60 H8 0.80 0.043 16.13* 0.35 0.028 9.40* 0.65 H9 0.62 0.053 11.00* 0.62 0.053 10.97* 0.34

H10 0.63 0.047 11.63* 0.60 0.039 11.23* 0.41 1 >t* 1.96

2 300

Cronbachs CRAVE0.50 (Bagozzi & Yi, 1988) SFL0.5Kline (2005) 0.85 FornellLarcker (1981) AVE (2) 0.17 ()0.73 () AVE

17

=2 693.47 001.

18

3

3 81.6% 18.4% 1 38.2%35 20-25 60.3% 26-35 18.9% (2011) 20000-40000 32.8% 1000 80% Nyman (2004)

19

76% 56.9% 1 51.7% 88.8% 39.9% 38.2% 1 49.8%

4 4 (skewness) (kurtosis) 3 10

(Kline, 2005) 4 (M=3.51)

(M=3.46) 1-5 T

( 96.2=t 003.=p ) Olsen (1996) (2011)

()

T

( 5) (Welte, Barnes, Wieczorek, Tidwell, & Parker, 2002)

Rantanen (2007) 3 %

116 18.4 514 81.6

1 241 38.2 1-3 161 25.7 4-6 95 15.1 7-9 37 5.8

20

10 96 15.2

20~25 380 60.3 26~35 119 18.9 36~45 54 8.6 46~55 53 8.5 56~65 21 3.3 65 3 0.4

()

123 19.6 20000 184 29.2 20000-40000 207 32.8 40001-60000 67 10.7 60001-80000 31 4.9 80001-100000 9 1.4 100000 9 1.3

() 33 5.3 91 14.5 479 76.0 24 3.8 3 0.4

4 0.7 41 6.5 27 4.3 13 2.0 67 10.6 13 2.0 18 2.9 16 2.6 16 2.6 358 56.9 16 2.6 6 0.9 35 5.4

1 326 51.7 1-2 127 20.2 2-3 71 11.3 3-4 106 16.8

556 88.2

21

74 11.8

()

251 39.9 241 38.2 138 21.9

()

100 201 31.9 110-300 126 20.0 310-500 86 13.6 510-1000 124 19.7 1010-2000 33 5.3 2010-3000 10 1.6 3010-4000 5 0.8 4010-5000 17 2.7 5010-10000 21 3.3 10010-100000 7 1.1

1 () 314 49.8 2-3 166 26.3 4-5 38 6.1 6 () 112 17.8

630

4

(M)

(SD)

1.00 5.00 3.02 0.83 -0.20 0.04 1.00 5.00 3.37 0.71 -0.03 0.15 1.33 5.00 3.67 0.69 -0.08 -0.37 1.20 5.00 3.89 0.61 -0.40 0.21 2.00 5.00 3.70 0.62 0.10 -0.56

1.50 5.00 3.51 0.66 -0.11 -0.12 1.00 5.00 3.46 0.66 0.12 -0.40

5

t

116 514

447.35 1752.80

962.31 8631.44

67.38 286.92 -10.20*

116 514 1.37 2.03

0.76 1.17

0.06 0.03 -4.43*

22

116 514

3.21 2.98

0.90 0.81

0.05 0.02 3.48*

116 514

3.39 3.35

0.72 0.71

0.05 0.02 0.65

116 514

3.73 3.66

0.68 0.69

0.04 0.02 1.21

116 514

3.79 3.91

0.59 0.61

0.04 0.02 -2.64*

116 514

3.71 3.69

0.54 0.63

0.04 0.02 0.49

05.0*

23

( =13 .66; 47.23 = )

( =14 .29) Snyder Ickes (1985)Stone (2001)

( =15 -.18) ( =25 .11)

( 5)

Prendergast Stole (1996)

24

40% (R-square =1-.60) 29% (R-square =1-.71) 40% (R-square =1-.60) 6% (R-square =1-.94)

Normative herding

Informational herding

H1

H2

H3

H4

H6

H5

H7

H8

H9

H10

.66*

.47*.22*

.29*

-.44*-.20*

.11*

.75*

.85*

.57*.55*

.63*

.78*

.76*

.77*

0.59*

0.59*

.70*

.60*

.40*

.43*

.40*

.65*

.65*

.29*

.44*

.68*

.60*

.71*

Neuroticism

O2

O1

E4

E3

E2

E1.54*

N1

C6

N2

N3

C5

C4

C3

C2

C1

A5

A4

A3

A2

A1

O3

Extraversion

Openness

Agreeableness

Conscientiousness

.24*

.79*.87*

.68*

.68*.67*

.76*

.78*

.64*.73*

.78*

.64*.84*

.82*

.75*

.63*

.63*

.71*

.71*

.66*

.67*

.77*

.38*

.25*

.54*

.55*

.42*

.40*

.59*

.46*

.39*

.58*

.30*

.33*

.44*

.60*

.61*

.50*

.49*

.56*

.55*

.41*

-.18*

C7

C8

C9

.37*

.47*

.49*

.79*

.73*

.72*

* 96.1>t

4

25

Age

Betting experience

Betting Frequency

Level of education

Working experience

Normative herding

Informational herding

H6

H5

H4

H3

H2

H7

H8

H9

H10

-.12*

0.18*

-0.14

*

.60*

.09*

-.16*.09*

-.10*

.70*

.84*

.59*

.56*

.67*

.80*

.77*

.80*

.59*.64*

.30*

.65*

.69*

.55*

.36*

.41*

.36*

.66*

.59*

1.00*

1.00*

1.00*

1.00*

1.00*

.94*

Occupation

Income

Channel

Betting amount

Gender1.00*

1.00*

1.00*

1.00*

1.00*

H1 .50*

.15*

0.18*

.12*

* 96.1>t

5

1 1000

26

(2009)

35

(Welte et al., 2002)

Marotta (2008)

27

(cross-validation)

(

(disposition effect) (overconfidence) )

Lamb (2002) Rantanen (2007) Allemand (2007)

1. (2003)

2. 2006344417-444

3. (2011)1045-65

4. (2006)

28

5. (2009)

8(2)230-238 6. (2013) ( 101 ) 2013

7 25 https://www.sac.gov.tw/WebData/WebData.aspx?wmid=915&WDID=3123

7. (2009) 38 (1)61-66

8. (2009)

9. (2006) -2004 8 (2)37-50

10. (2010) -71-13

11. (2008) 12. (2003)

6 (1)51-72 13. (2004)

14. (2008)

15. (2002) 16. (2009)

17. (2007)

18. Aasved, M. (2003). The sociology of gambling. Springfield, IL: Charles

29

C. Thomas. 19. Adams, D. (2001). My ticket, my self: Lottery ticket number selection

and the commodification and extension of the self. Sociological Spectrum, 21, 455-477.

20. Allemand, M., Zimprich, D., & Hertzog, C. (2007). Cross-sectional age differences and longitudinal age changes of personality in middle adulthood and old age. Journal of Personality, 75(2), 323-358.

21. Allen, V. L. (1965). Situational factors in conformity, In Berkowitz, L. ed., Advances in experimental social psychology, New York: Academic Press.

22. Allport, G. W. (1937). Personality: A psychological interpretation. New York: Holt, Rinehart & Winson.

23. Anderson, J. C. & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411-423.

24. Ariyabuddhiphongs, V. (2006). A test of the social cognitive model of lottery gambling in Thailand. International Gambling Studies, 6, 77-93.

25. Ariyabuddhiphongs, V. (2011). Lottery gambling: A review. Journal of Gambling Studies, 27, 15-33.

26. Ariyabuddhiphongs, V., & Chanchalermporn, N. (2007). A test of social cognitive theory reciprocal and sequential effects: Hope, superstitious belief and environmental factors among lottery gamblers in Thailand, Journal of Gambling Studies, 23, 201-214.

27. Asch, S. E. (1951). Effects of group pressure upon the modification and distortion of judgment. In Guetzkow, H. ed., Groups, leadership and men, Pittsburgh, PA: Carnegie Press.

28. Baddeley, M. (2010). Herding, social influence and economic decision-making: Socio-psychological and neuroscientific analyses, Philosophical Transactions of the Royal Society B: Biological Sciences, 365, 281-90.

29. Bagozzi, R. R. (1980). Causal models in marketing. New York: Wiley.

30

30. Bailard, T. E., Biehl, D. L., & Kaiser, R. W. (1986). Personal money management. 5th ed., Chicago, Ill.: Science Research Associates.

31. Balabanis, G. (2002). The relationship between lottery ticket and scratch-card buying behavior, personality and other compulsive behaviours. Journal of Consumer Behaviour, 2, 7-22.

32. Banerjee, A. (1992). A simple model of herd behaviour. Quarterly Journal of Economics, 107(3), 797-817.

33. Bearden, W. O., Netemeyer, R. G., & Teel, J. E. (1989). Measurement of consumer susceptibility to interpersonal influence. Journal of Consumer Research, 15, 473-481.

34. Bearden, W. O., & Rose, R. L. (1990). Attention to social comparison information: An individual difference factor affecting consumer conformity, Journal of Consumer Research, 16, 461-471.

35. Bikhchandani, S., Hirshleifer, D., & Welch, I. (1992). A theory of fads, fashion, custom, and cultural change as informational cascades. Journal of Political Economy, 100(5), 992-1026.

36. Bollen, K. A. (1989). Structural equations with latent variables. New York: Wiley.

37. Browne, B. A., & Brown, D. J. (1994). Predictors of lottery gambling among American college students. Journal of Social Psychology, 134, 339347.

38. Bruyneel, S., Dewitte, S., Franses, P. H., & Dekimpe, M. G. (2006). Why consumer buy lottery tickets when the sun goes down on them. The depleting nature of weather-induced bad moods. Advances in Consumer Research, 33, 46-47.

39. Caplin, A., & Leahy, J. (2001). Psychological expected utility theory and anticipatory feelings. Quarterly Journal of Economics, 116, 55-79.

40. Chantal, Y., & Vallerand, R. J. (1996). Skill versus luck: A motivational analysis of gambling involvement. Journal of Gambling Studies, 12, 407418.

41. Clotfelter, C. T., & Cook, P. J. (1989). Selling hope: State lotteries in

31

America. Cambridge, MA: National Bureau of Economic Research. Working Paper No. 2928.

42. Clotfelter, C. T., & Cook, P. J. (1990). On the economics of state lotteries. Journal of Economic Perspectives, 4(4), 105-119.

43. Clotfelter, C. T., & Cook, P. J. (1993). The gamblers fallacy in lottery play. Management Science, 39, 1521-1525.

44. Cook, M., McHenry, R., & Leigh, V. (1998). Personality and the national lottery, Personality and Individual Differences, 25, 49-55.

45. Costa, P. T. Jr., & McCrae, R. R. (1992). Professional manual for the NEO PI-R and NEO-FEI. Odessa, FL: Psychological Assessment Resources, Inc.

46. Coups, E., Haddock, G., & Webley, P. (1998). Correlates and predictors of lottery play in the United Kingdom. Journal of Gambling Studies, 14, 285-303.

47. Crutchfield, R. A. (1955). Conformity and character. American Psychologist, 10, 191-198.

48. Daft, R. L. (2003). Organization theory and design. 8th ed., Cincinnati: South-Western.

49. DellaVigna, S. (2009). Psychology and economics: Evidence from the field. Journal of Economic Literature, 47(2), 315-372.

50. Eagly, A. H., & Carli, L. L. (1981). Sex of researchers and sex typed communications as determinants of sex differences in influence ability: A meta-analysis of social influence studies. Psychological Bulletin, 90, 1-20.

51. Elster, J. (1998). Emotions and economic theory. Journal of Economic Literature, 36, 47-74.

52. Fama, E. F. (1965). The behavior of stock market prices. The Journal of Business, 38, 34-105.

53. Fornell, C., & Larcker, D. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18, 39-50.

32

54. Forrest, D., & Guley, O. D. (2009). Participation and level of play in the UK National Lottery and correlation with spending on other modes of gambling. International Gambling Studies, 9, 165-178.

55. Forrest, D., & Simmons, R. (2003). Sport and Gambling. Oxford Review of Economic Policy, 19(4), 598-611.

56. Forrest, D., & Simmons, R., & Chesters, N. (2002). Buying a dream: Alternative models of demand for lotto. Economic Inquiry, 40, 485-496.

57. Fung, H. H., & Ng, S. K. (2006). Age differences in the sixth personality factor: Age differences in interpersonal relatedness among Canadians and Hong Kong Chinese. Psychology & Aging, 21(4), 810-814.

58. Graeme, E. (1995). The national lottery: Planning for leisure or pay up and play the game? Leisure Studies, 14(4), 225-244.

59. Griffiths, M., & Wood, R. (2001). The psychology of lottery gambling. International Gambling Studies, 1, 27-45.

60. Griffiths, M., Wardle, H., Orford, J., Sproston, K., & Erens, B. (2009). Sociodemographic correlates of Internet gambling: Findings from the 2007 British gambling prevalence survey. CyberPsychology & Behavior, 12, 199202.

61. Gupta, R., & Derevensky, J. (1997). Familial and social influences on juvenile gambling behavior. Journal of Gambling Studies, 13, 179192.

62. Guryan, J., & Kearney, M. S. (2008). Gambling at lucky stores: Empirical evidence from state lottery sales. The American Economic Review, 98(1), 458-473.

63. Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (6th ed.). Upper Saddle River, NJ: Person Prentice Hall.

64. Hammond, J. S., Keeney, R. L., & Raiffa, H. (2002). Smart choices: A practical guide to making better life decisions. Boston Mass: Harvard Business School Press.

65. Herring, M., & Bledsoe, T. (1994). A model of lottery participation: Demographics, context, and attitudes. Policy Studies Journal, 22,

33

245257. 66. Hing, N., & Breen, H. (2001). Profiling lady luck: An empirical study of

gambling and problem gambling amongst female club members. Journal of Gambling Studies, 17, 47-69.

67. Jackson, R. (1994). Demand for lottery products in Massachusetts. Journal of Consumer Affairs, 28(2), 313-325.

68. Jahoda, M. (1959). Conformity and independence: A psychological analysis. Human Relations, 12(2), 99-120.

69. Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291.

70. Kaizeler, M. J., & Faustino, H. (2008). Lottery sales and per-capita GDP: An inverted U relationship. Lisbon, Portugal: Technical University of Lisbon, School of Economics and Management. Working Paper No. WP41/2008/DE/SOCIUS.

71. Kitchen, H., & Powells, S. (1991). Lottery expenditures in Canada: A regional analysis of determinants and incidence. Applied Economics, 23(12), 1845-1852.

72. Kline, R. B. (2005). Principles and practice of structural equation modeling (2nd ed.). New York: Guilford.

73. Lam, D. (2007). An exploratory study of gambling motivations and their impact on the purchase frequencies of various gambling products. Psychology & Marketing, 24, 815-827.

74. Lamb, M. E., Chuang, S. S., Wessels, H., Broberg, A. G., & Huang, C. P. (2002). Emergence and construct validation of the big five factors in early childhood: A longitudinal analysis of their ontogeny in Sweden, Child Development, 73(3), 1517-1524.

75. Lascu, D., & Zinkhan, G. M. (1999). Consumer conformity: Review and applications for marketing theory and practice. Journal of Marketing Theory and Practice, 7(3), 1-12.

76. Lim, S., & Lee, J. E. R. (2009). When playing together feels different: effects of task types and social contexts on physiological arousal in

34

multiplayer online gaming contexts. CyberPsychology & Behavior, 12, 5961.

77. Lochbaum, M. R., Rhodes, R. E., Stevenson, S. J., Surlesd, J., Stevens, T., & Wang, C. K. J. (2010). Does gender moderate the exercising personality? An examination of continuous and stage-based exercise. Psychology, Health & Medicine, 15(1), 50-60.

78. Macinnis, H. (1997). Consumer behavior. New York: Houghton Mifflin Company.

79. Marotta, D. J. (2008). Behavioral finance: Herd mentality. The Central New York Business Journal, 22(33), 23.

80. Matheson, V. A. (2001). When are state lotteries a good bet (revisited)? Eastern Economic Journal, 27, 55-70.

81. McNeilly, D. P., & Burke, W. J. (2001). Gambling as a social activity of older adults. International Journal for Aging and Human Development, 52(1), 19-28.

82. Mintzberg, H., Raisinghani, O., & Theoret, A. (1976). The structure of unstructured decision processes. Administrative Science Quarterly, 21, 1976, 246-275.

83. Miyazaki, A. D., Brumbaugh, A. M., & Sprott, D. E. (1999). Government-sponsored lotteries: Exploring purchase and nonpurchase motivations. Psychology & Marketing, 16, 1-20.

84. Moore, S. M., & Ohtsuka, K. (1997). Gambling activities of young Australians: Developing a model of behaviour. Journal of Gambling Studies, 13, 207236.

85. Myers, I. B., & McCaulley, M. H. (1985). Manual: A guide to the development and use of the Myer Briggs Type Indicator. Palo Alto, CA: Consulting Psychologist Press, Inc.

86. Nicholson, N., Soane, E., Fenton-O'Creevy, M., & Willman, P. (2005). Personality and domain-specific risk taking. Journal of Risk Research, 8(2), 157-176.

87. Nyman, J. A. (2004). A theory of demand for gambles. Department of

35

Economics Working Paper #322. University of Minnesota, Minneapolis. 88. Menkhoff, L., Schmidt, U. & Brozynski, T. (2006). The impact of

experience on risk taking, overconfidence, and herding of fund managers: Complementary survey evidence. European Economic Review, 50, 1753-1766.

89. Olsen, R. A. (1996). Implications of herding behavior for earnings estimation, risk assessment, and stock returns. Financial Analysts Journal, 52 (4), 37-41.

90. Osland, J. S., Kolb, D. A., Rubin, I. M., & Turner, M. E. (2006), Organizational behavior: An experiential approach. 8th ed., New Jersey: Prentice- Hall.

91. Papachristou, G. (2004). The Birtish gamblers fallacy. Applied Economics, 36(18), 2073-2077.

92. Park, W. C., & Lessig, P. V. (1977). Students and housewives: Differences in susceptibility to reference group influence. Journal of Consumer Research, 4, 102-110.

93. Pelletier, M. F., & Ladouceur, R. (2007). The effect of knowledge of mathematics on gambling behaviours and erroneous perceptions. International Journal of Psychology, 42, 134-140.

94. Pervin, L. A. (1993). Personality: Theory and research. 6th ed., New York: John Wily and Sons.

95. Prendergast, C., & Stole, L. (1996). Impetuous youngsters and jaded old-timers: Acquiring a reputation for learning. Journal of Political Economy, 194, 1105-1134.

96. Rantanen, J., Metsapelto, R., Feldt, T., Pulkkinen, L., & Kokko, K. (2007). Long-term stability in the Big Five personality traits in adulthood. Scandinavian Journal of Psychology, 48, 511-518.

97. Robbins, S. P. (2002). Management, New Jersey: Pearson Prentice-Hall. 98. Rogers, P. (1998). The cognitive psychology of lottery gambling: A

theoretical review. Journal of Gambling Studies, 14, 111-134. 99. Rotter, J. B. (1966). Generalized expectancies for internal versus

36

external control of reinforcements. Psychological Monographs, 80, 1-27. 100. Schaefer, P. S., Williams C. C., Goodie, A. S., & Campbell, W. K.

(2004). Overconfidence and the Big Five. Journal of Research in Personality, 38, pp. 473-480,.

101. Sias, W. R. (2004). Institutional herding. The Review of Financial Studies, 17(1), 165-206.

102. Schreurs, B., Druart, C., Proost, K., & De Witte, K. (2009). Symbolic attributes and organizational attractiveness: The moderating effects of applicant personality. International Journal of Selection and Assessment, 17(1), 35-46.

103. Schumacker, R. E., & Lomax, R. G. (1996). A beginner's guide to structural equation modeling. Mahwah, NJ: Lawrence Erlbaum Associates.

104. Sehgal, S., & Tripathi, N. (2009). Investment strategies of FIIs in the Indian equity market. The Journal of Business Perspective, 13(1), 11-18.

105. Sevigny, S., & Ladoucer, R. (2003). Gamblers irrational thinking about chance events: The double switching concept. International Gambling Studies, 3, 149-161.

106. Shafir. E, & LeBoeuf, R. A. (2002). Rationality. Annual Review of Psychology, 53(1), 491517.

107. Sherif, M. (1966). The psychology of social norms. New York: Harper and Brothers.

108. Simon, H.A. (1956). Models of bounded rationality. Economic Analysis and Public Policy, Cambridge, Mass., MIT Press, Vol. 1, Reprinted in 1982, 235-44.

109. Snyder, M., & Ickes, W. (1985). Personality and social behavior. In Lindzey, G. and Aronson, E. eds., Handbook of social psychology, New York: Random House.

110. Stinchfield, R., Cassuto, N., Winters, K., & Latimer, W. (1997). Prevalence of gambling among Minnesota public school students in 1992 and 1995. Journal of Gambling Studies, 13, 2548.

37

111. Stone, E. R., Dodrill, C. L., & Johnson, N. (2001). Depressive cognition: A test of depressive realism versus negativity using general knowledge questions. Journal of Personality, 135(6), 583-602.

112. Terrell, D. (1994). A test of the gamblers fallacy: Evidence form pari-mutuel games. Journal of Risk and Uncertainty, 8(3), 309-317.

113. Trevorrow, K., & Moore, S. (1998). The association between loneliness, social isolation and womens electronic gaming machine gambling. Journal of Gambling Studies, 14(3), 263-284.

114. Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185, 1124-1131.

115. Tversky, A., & Kahneman, D. (1981). The framing of decisions and the psychology of choice. Science, 211, 453-458.

116. Vander Bilt, J., Dodge, H. H., Pandav, R., Shaffer, H. J., & Ganguli, M. (2004). Gambling participation and social support among older adults: A longitudinal community study. Journal of Gambling Studies, 20(4), 373-390.

117. Welte, J. W., Barnes, G. M., Wieczorek, W. F., Tidwell, M.-C. O., & Parker, J. C. (2002). Gambling participation in the U.S.- Results from a national survey. Journal of Gambling Studies, 18, 313-337.

118. Wickwire, E. M., Jr., Whelan, J. P., West, R., Meyer, A., McCausland, C., & Luellen, J. (2007). Perceived availability, risks, and benefits of gambling among college students. Journal of Gambling Studies, 23, 395-408.

119. Wilkie, W. L. (1994). Consumer behavior. 3rd ed., New York: John Wiley and Sons Inc.

120. Williams, R. J., & Connolly, D. (2006). Does learning about the mathematics of gambling change gambling behavior. Psychology of Addictive Behaviors, 20, 62-68.

121. Williams, L. V. (2005). Weak form information efficiency in betting markets. In Information Efficiency in Financial and Betting Markets, edited by L. V. Williams. Cambridge: Cambridge University Press.

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